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Get PDF奈良先端科学技術大学院大学修士(工学)master thesi
Interpretable Neural Machine Translation from Translation to Post-Editing
Get PDF奈良先端科学技術大学院大学博士(工学)doctoral thesi
Perovskite Thin Film Fabricated from Radio Frequency Sputtering towards Future Solar Cell Applications
Get PDF奈良先端科学技術大学院大学博士(工学)doctoral thesi
Practicality of in-kernel/user-space packet processing empowered by lightweight neural network and decision tree
No full textIntegrating machine learning (ML) into kernel packet processing, such as extended Berkeley Packet Filter (eBPF) and eXpress Data Path (XDP), represents a promising strategy for achieving fast and intelligent networking on generic hardware. This includes tasks like automating network operations and discerning traffic classification, exemplified by intrusion detection systems (IDS) combining Decision Tree (DT) and eBPF. However, the potential of ML-empowered packet processing remains to be fully explored. To ensure the integrity and security of kernel operations, eBPF/XDP programs must adhere to stringent constraints such as the maximum number of jump instructions, maximum stack space, and exclusion of floating-point arithmetic. These constraints pose challenges for implementing more intricate ML techniques (e.g., neural networks (NNs)) within eBPF/XDP programs. In such scenarios, AF_XDP provides an alternative solution by allowing XDP programs to redirect packets to user-space applications, bypassing the network stack. This paper initiates an exploration into fast packet classification through two distinct approaches: (1) an in-kernel approach employing eBPF/XDP and (2) a user-space approach assisted by AF_XDP. Specifically, to tackle the eBPF constraints, the in-kernel NN classifier adopts (1) quantization of trained model in the user space, (2) executing the integer-arithmetic-only NN within the kernel space, and (3) sequential layer operations through tail calls. These approaches are evaluated based on factors including packet processing speed, resource efficiency, and detection performance. Notably, our experimental findings demonstrate that (1) Classifiers relying solely on integer arithmetic, such as NN and DT, significantly reduce inference time while maintaining binary classification performance; (2) The lightweight NN classifier can improve the detection performance for most of attacks in case of the multi-class classification compared to the lightweight DT classifier; (3) In single-core scenarios, the DT-empowered in-kernel method can almost achieve the maximum packets per second (pps), i.e., about 800,000 pps, whereas the NN-empowered one exhibits lower pps (i.e., about 450,000 pps); (4) In multi-core scenarios, the NN-empowered packet processing can almost achieve the maximum pps with two or more cores in the AF_XDP approach and four or more cores in the in-kernel approaches.journal articl
Dual Role of AgNO3 as an Oxidizer and Chloride Remover toward Enhanced Combustion Synthesis of Low-Voltage and Low-Temperature Amorphous Rare Metal-Free Oxide Thin-Film Transistors
No full textSnO2 transistors show great promise as an alternative to existing In2O3-based transistors, considering their abundance and similar electronic properties. However, they suffer from highly negative on-voltages, large subthreshold swings, and high processing temperatures. One of the reasons for this is the residual chloride in the SnO2 film, which negatively impacts the transistor by increasing the defects or acting as a dopant, thereby shifting the turn-on voltage negatively and increasing the subthreshold swing. Herein, we present a facile method of producing SixSnyO films with fewer chloride impurities, which can be used in high-performance, solution-processed TFTs. We employed AgNO3 as an oxidizer for a low-temperature combustion reaction at 300 °C, which simultaneously acts as a chloride remover. We successfully reduced the turn-on voltage from 22120.7 V using this route. The subthreshold swing was decreased from 2.91 to 0.32 V/dec using the same Sn concentration. The highest mobility obtained was 1.92 cm2/(V s) from the 0.25 M Sn precursor at a low drain voltage of 0.1 V. This method can be used as a general route for fabricating solution process-based SnO2 TFTs and further expanding its application to flexible devices via low-temperature combustion.journal articl
Cascading and amplified effects in fluorescence photoswitching - towards sensitive molecular dosimeters for radiation detection
Get PDF奈良先端科学技術大学院大学博士(理学)doctoral thesi
Egg-Laying Robot to Enhance Mind Perception of Children and Parents
Get PDFThe lifelikeness of social robots is important for building more natural relationships with humans. Although the lifelikeness of the way a robot behaves and its appearance has been explored, few studies have focused on mimicking the life cycle. In this study, we focused on egg-laying, one of the life cycles, and developed a robot capable of simulated egg-laying. Using the developed robot, we experimentally evaluated the effects of egg-laying behavior on the robot's lifelikeness and mind perception. After observing the egg-laying, there was no statistically significant difference in the lifelikeness, however, the children and parents of the participants in the experiment perceived the robot's mind significantly more.conference pape
Analyzing user reactions using relevance between location information of tweets and news articles
No full textIn this study, we analyze the extent of user reactions based on user’s tweets to news articles, demonstrating the potential for home location prediction. To achieve this, we quantify users’ reactions to specific news articles based on the textual similarity between tweets and news articles, showcasing that users’ reactions to news articles about their cities are significantly higher than those about other cities. To maximize the difference in reactions, we introduce the concept of News Distinctness, which highlights the news articles that affect a specific location. By incorporating News Distinctness with users’ reactions to the news, we magnify its effects. Through experiments conducted with tweets collected from users whose home locations are in five representative cities within the United States and news articles describing events occurring in those cities, we observed a 6.75% to 40% improvement in the reaction score when compared to the average reactions towards news for outside of home location, clearly predicting the home location. Furthermore, News Distinctness increases the difference in reaction score between news in the home location and the average of the news outside of the home location by 12% to 194%. These results demonstrate that our proposed idea can be utilized to predict the users’ location, potentially recommending meaningful information based on the users’ areas of interest.journal articl
DNA-based Nanonetworks: Realizing the Internet of Bio-Nano Things
No full textvideo/mp4The Internet of Bio-Nano Things (IoBNT) is an innovative field of research located at the intersection of nanotechnology, biotechnology and information and communication technologies. It aims to enable the seamless integration of biological and nanoscale systems into the Internet in order to develop advanced biomedical applications, environmental monitoring sensors and energy-efficient networks. At the core of IoBNT are biocompatible nanodevices that can function in living organisms to monitor or modify specific biological processes in real time. These devices communicate with each other and with the Internet to collect, process and transmit data, opening up entirely new possibilities for health monitoring, disease control, environmental protection and many other areas. By merging biology and nanotechnology, IoBNT promises to push the boundaries of what is technically possible while improving the efficiency and sustainability of technological solutions.DNA-based nanonetworks are a promising concept and implementation technology for the IoBNT. In this approach DNA is manipulated to form structures known as tiles, which self-assemble to much more complex structures such as nano devices and even full nano networks which function autonomously. Such networks communicate through molecular messages which are, in the very same way, also made of tiles. Such messages are even able to perform computations which can be used for disease detection and treatment.In this talk, we will give a brief introduction into the IoBNT, but will then mainly concentrate on DNA-based nanonetworks. We introduce the basic principles, especially DNA tiles, self assembly, and in-message computation. We explain, using a few examples, how such networks can be of use in medical applications, e.g. by dispensing medication exactly at the position in the body where it is needed. Finally we present first ideas for wet lab experiments and give an outlook on future work.講演日: 2024年5月29日講演場所: エーアイ大講義室, AI Inc. Seminar Hall （L1）vide